Senior Backend Engineer for ML Infrastructure and Reliability
Design, build, and operate production-grade Django services for high-throughput ML inference. Ensure reliability, observability, and performance. Collaborate with ML and backend engineers.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Senior Backend Engineer, ML Infrastructure & Reliability
A rare opportunity has opened for an experienced Senior Backend Engineer to own and scale backend systems powering high-throughput ML inference for a growing AI platform.
In this role, you will design, build, and operate production-grade Django services that orchestrate ML workflows across internal systems and external providers. You will take end-to-end ownership of reliability, observability, and performance, ensuring that the platform scales safely as usage grows.
If you enjoy tackling complex reliability and orchestration challenges and building backend systems that must perform at scale…
Feel invited — this role offers real ownership and technical impact.
WHAT WE OFFER
- Full-time, B2B
- 100% remote
- High-ownership over core backend infrastructure
- Collaboration with ML and backend engineers
- Exposure to high-throughput, distributed ML workflows
- Pragmatic, product-driven engineering culture
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YOUR ROLE
- Build and maintain Django services for ML inference workflows
- Implement asynchronous execution with queues, workers, and schedulers
- Ensure reliability: idempotency, retries, rate limiting, backpressure
- Define and operate SLOs/SLAs; lead incident response and postmortems
- Implement end-to-end observability: metrics, logs, traces, dashboards, alerts
- Collaborate with ML engineers to productionize pipelines
- Support infrastructure with Terraform and CI/CD
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IF YOU ARE A PERSON WHO
- Has strong experience as a Python backend engineer with production ownership
- Has hands-on experience running Django in production (ORM, migrations, request lifecycle, performance tuning)
- Has built and operated asynchronous job systems
- Understands distributed system reliability and orchestration patterns
- Knows Linux, networking, and cloud platforms (AWS/GCP)
- Has practical experience with Infrastructure as Code
- Has operated ML infrastructure at scale or worked with MLOps tooling (nice to have)
- Thrives in high-ownership, fast-paced environments
Congrats! This role is ideal for YOU!
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